Reducing the dimensions or size of a search window in a computer vision tracking processes may decrease processing time, reduce mismatches and increase predictive results of the tracking. However, reducing dimensions of a search window may increase the chances of losing the tracked object, for example, when the object moves too quickly and as a result exceeds the boundaries of the search window. Defining a proper size or dimension for the search window may therefore balance these factors.
FIG. 1 illustrates a prior art method for determining the size of a search window 100 in a tracking method. Known tracking methods rely on a rule of thumb for sizing search window 100 that sets window 100 dimension around the last tracked position of a tracked object 110 according to the following formula:Window Size=(2X+tracked Object Width)*(2Y+tracked Object Height)  Formula 1
Usually search window 100 is created around the last tracked position of tracked object 110 where X & Y are the full range, in the respective directions, that the object may reach in the next scanned frame. This may be calculated based on the last known velocity of the object and the maximum distance, in all possible directions, it may reach over the time between capturing of frames by the tracking system. Thus, for example, if the object is moving in high velocity, the values of X and Y will grow linearly with the velocity and the area of the search window may grow to the power of 2, thus being very large.